{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FSRS4Anki Optimizer Easy & Hard Factor\n",
    "\n",
    "[![open in colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/open-spaced-repetition/fsrs4anki/blob/main/archive/candidate/easy-hard-factor.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here are some settings that you need to replace before running this optimizer.\n",
    "\n",
    "filename = \"../collection-2022-09-18@13-21-58.colpkg\"\n",
    "# If you upload deck file, replace it with your deck filename. E.g., ALL__Learning.apkg\n",
    "# If you upload collection file, replace it with your colpgk filename. E.g., collection-2022-09-18@13-21-58.colpkg\n",
    "\n",
    "# Replace it with your timezone. I'm in China, so I use Asia/Shanghai.\n",
    "# You can find your timezone here: https://gist.github.com/heyalexej/8bf688fd67d7199be4a1682b3eec7568\n",
    "timezone = 'Asia/Shanghai'\n",
    "\n",
    "# Replace it with your Anki's setting in Preferences -> Scheduling.\n",
    "next_day_starts_at = 4\n",
    "\n",
    "# Replace it if you don't want the optimizer to use the review logs before a specific date.\n",
    "revlog_start_date = \"2006-10-05\"\n",
    "\n",
    "# Set it to True if you don't want the optimizer to use the review logs from suspended cards.\n",
    "filter_out_suspended_cards = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import zipfile\n",
    "import sqlite3\n",
    "import time\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import math\n",
    "from typing import List, Optional\n",
    "from datetime import timedelta, datetime\n",
    "import statsmodels.api as sm\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "import torch\n",
    "from torch import nn\n",
    "from torch import Tensor\n",
    "from torch.utils.data import Dataset, DataLoader, Sampler\n",
    "from torch.nn.utils.rnn import pad_sequence, pack_padded_sequence, pad_packed_sequence\n",
    "from sklearn.model_selection import StratifiedGroupKFold\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from itertools import accumulate\n",
    "from tqdm.auto import tqdm\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
    "tqdm.pandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Deck file extracted successfully!\n",
      "revlog.csv saved.\n",
      "Trainset saved.\n",
      "Retention calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "572b5478ab0447838cfc842898e02bd3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/26286 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stability calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4140061ddb3c4a21b02fece295dab479",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "analysis:   0%|          | 0/489 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analysis saved!\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "      r_history  avg_interval  avg_retention  stability  factor  group_cnt\n",
      "              1           1.1          0.892        1.0     inf       2063\n",
      "            1,3           3.1          0.920        4.0    4.00       1600\n",
      "          1,3,3           7.1          0.910        7.9    1.98       1320\n",
      "        1,3,3,3          16.6          0.862       10.8    1.37        986\n",
      "      1,3,3,3,3          36.5          0.840       22.3    2.06        659\n",
      "    1,3,3,3,3,3          77.0          0.861       36.4    1.63        358\n",
      "  1,3,3,3,3,3,3         117.9          0.906       38.5    1.06        177\n",
      "              2           1.0          0.902        1.1     inf        240\n",
      "            2,3           3.5          0.946        8.2    7.45        201\n",
      "          2,3,3          11.4          0.890        7.6    0.93        162\n",
      "              3           1.1          0.977        5.0     inf       4669\n",
      "            3,3           3.3          0.967       12.0    2.40       4211\n",
      "          3,3,3           8.1          0.960       19.9    1.66       3757\n",
      "        3,3,3,3          18.3          0.941       41.5    2.09       2834\n",
      "      3,3,3,3,3          35.2          0.930       50.5    1.22       1761\n",
      "    3,3,3,3,3,3          64.9          0.929       97.9    1.94       1102\n",
      "  3,3,3,3,3,3,3         100.9          0.949      143.0    1.46        530\n",
      "3,3,3,3,3,3,3,3         133.6          0.990     1821.9   12.74        131\n",
      "              4           2.0          0.976       10.7     inf       2789\n",
      "            4,3           3.7          0.976       20.4    1.91       2293\n",
      "          4,3,3           8.3          0.967       32.5    1.59       2051\n",
      "        4,3,3,3          19.8          0.958       54.5    1.68       1700\n",
      "      4,3,3,3,3          41.0          0.958       99.5    1.83       1148\n",
      "    4,3,3,3,3,3          68.1          0.956      116.1    1.17        521\n",
      "  4,3,3,3,3,3,3          78.5          0.979      110.7    0.95        248\n",
      "4,3,3,3,3,3,3,3         114.1          0.984      177.8    1.61        166\n"
     ]
    }
   ],
   "source": [
    "\"\"\"Step 1\"\"\"\n",
    "# Extract the collection file or deck file to get the .anki21 database.\n",
    "with zipfile.ZipFile(f'{filename}', 'r') as zip_ref:\n",
    "    zip_ref.extractall('./')\n",
    "    print(\"Deck file extracted successfully!\")\n",
    "\n",
    "\"\"\"Step 2\"\"\"\n",
    "if os.path.isfile(\"collection.anki21b\"):\n",
    "    os.remove(\"collection.anki21b\")\n",
    "    raise Exception(\n",
    "        \"Please export the file with `support older Anki versions` if you use the latest version of Anki.\")\n",
    "elif os.path.isfile(\"collection.anki21\"):\n",
    "    con = sqlite3.connect(\"collection.anki21\")\n",
    "elif os.path.isfile(\"collection.anki2\"):\n",
    "    con = sqlite3.connect(\"collection.anki2\")\n",
    "else:\n",
    "    raise Exception(\"Collection not exist!\")\n",
    "cur = con.cursor()\n",
    "res = cur.execute(f\"\"\"\n",
    "SELECT *\n",
    "FROM revlog\n",
    "WHERE cid IN (\n",
    "    SELECT id\n",
    "    FROM cards\n",
    "    {\"WHERE queue != -1\" if filter_out_suspended_cards else \"\"}\n",
    ")\n",
    "\"\"\"\n",
    ")\n",
    "revlog = res.fetchall()\n",
    "if len(revlog) == 0:\n",
    "    raise Exception(\"No review log found!\")\n",
    "df = pd.DataFrame(revlog)\n",
    "df.columns = ['id', 'cid', 'usn', 'r', 'ivl', 'last_lvl', 'factor', 'time', 'type']\n",
    "df = df[(df['cid'] <= time.time() * 1000) &\n",
    "        (df['id'] <= time.time() * 1000)].copy()\n",
    "\n",
    "df_set_due_date = df[(df['type'] == 4) & (df['ivl'] > 0)]\n",
    "df.drop(df_set_due_date.index, inplace=True)\n",
    "\n",
    "df['create_date'] = pd.to_datetime(df['cid'] // 1000, unit='s')\n",
    "df['create_date'] = df['create_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df['review_date'] = pd.to_datetime(df['id'] // 1000, unit='s')\n",
    "df['review_date'] = df['review_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df.drop(df[df['review_date'].dt.year < 2006].index, inplace=True)\n",
    "df.sort_values(by=['cid', 'id'], inplace=True, ignore_index=True)\n",
    "\n",
    "df['is_learn_start'] = (df['type'] == 0) & (df['type'].shift() != 0)\n",
    "df['sequence_group'] = df['is_learn_start'].cumsum()\n",
    "last_learn_start = df[df['is_learn_start']].groupby('cid')['sequence_group'].last()\n",
    "df['last_learn_start'] = df['cid'].map(last_learn_start).fillna(0).astype(int)\n",
    "df['mask'] = df['last_learn_start'] <= df['sequence_group']\n",
    "df = df[df['mask'] == True].copy()\n",
    "df.drop(columns=['is_learn_start', 'sequence_group', 'last_learn_start', 'mask'], inplace=True)\n",
    "df = df[(df['type'] != 4)].copy()\n",
    "\n",
    "type_sequence = np.array(df['type'])\n",
    "time_sequence = np.array(df['time'])\n",
    "df.to_csv(\"revlog.csv\", index=False)\n",
    "print(\"revlog.csv saved.\")\n",
    "\n",
    "df = df[(df['type'] != 3) | (df['factor'] != 0)].copy()\n",
    "df['real_days'] = df['review_date'] - timedelta(hours=int(next_day_starts_at))\n",
    "df['real_days'] = pd.DatetimeIndex(df['real_days'].dt.floor('D', ambiguous='infer', nonexistent='shift_forward')).to_julian_date()\n",
    "df.drop_duplicates(['cid', 'real_days'], keep='first', inplace=True)\n",
    "df['delta_t'] = df.real_days.diff()\n",
    "df.dropna(inplace=True)\n",
    "df['i'] = df.groupby('cid').cumcount() + 1\n",
    "df.loc[df['i'] == 1, 'delta_t'] = 0\n",
    "df = df.groupby('cid').filter(lambda group: group['type'].iloc[0] == 0)\n",
    "df['prev_type'] = df.groupby('cid')['type'].shift(1).fillna(0).astype(int)\n",
    "df['helper'] = ((df['type'] == 0) & ((df['prev_type'] == 1) | (df['prev_type'] == 2)) & (df['i'] > 1)).astype(int)\n",
    "df['helper'] = df.groupby('cid')['helper'].cumsum()\n",
    "df = df[df['helper'] == 0]\n",
    "del df['prev_type']\n",
    "del df['helper']\n",
    "\n",
    "def cum_concat(x):\n",
    "    return list(accumulate(x))\n",
    "\n",
    "t_history = df.groupby('cid', group_keys=False)['delta_t'].apply(lambda x: cum_concat([[int(i)] for i in x]))\n",
    "df['t_history']=[','.join(map(str, item[:-1])) for sublist in t_history for item in sublist]\n",
    "r_history = df.groupby('cid', group_keys=False)['r'].apply(lambda x: cum_concat([[i] for i in x]))\n",
    "df['r_history']=[','.join(map(str, item[:-1])) for sublist in r_history for item in sublist]\n",
    "df = df.groupby('cid').filter(lambda group: group['id'].min() > time.mktime(datetime.strptime(revlog_start_date, \"%Y-%m-%d\").timetuple()) * 1000)\n",
    "df['y'] = df['r'].map(lambda x: {1: 0, 2: 1, 3: 1, 4: 1}[x])\n",
    "df.to_csv('revlog_history.tsv', sep=\"\\t\", index=False)\n",
    "print(\"Trainset saved.\")\n",
    "\n",
    "df['retention'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['y'].transform('mean')\n",
    "df['total_cnt'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['id'].transform('count')\n",
    "print(\"Retention calculated.\")\n",
    "\n",
    "df = df.drop(columns=['id', 'cid', 'usn', 'ivl', 'last_lvl', 'factor', 'time', 'type', 'create_date', 'review_date', 'real_days', 'r', 't_history', 'y'])\n",
    "df.drop_duplicates(inplace=True)\n",
    "df['retention'] = df['retention'].map(lambda x: max(min(0.99, x), 0.01))\n",
    "\n",
    "def cal_stability(group: pd.DataFrame) -> pd.DataFrame:\n",
    "    group_cnt = sum(group['total_cnt'])\n",
    "    if group_cnt < 10:\n",
    "        return pd.DataFrame()\n",
    "    group['group_cnt'] = group_cnt\n",
    "    if group['i'].values[0] > 1:\n",
    "        r_ivl_cnt = sum(group['delta_t'] * group['retention'].map(np.log) * pow(group['total_cnt'], 2))\n",
    "        ivl_ivl_cnt = sum(group['delta_t'].map(lambda x: x ** 2) * pow(group['total_cnt'], 2))\n",
    "        group['stability'] = round(np.log(0.9) / (r_ivl_cnt / ivl_ivl_cnt), 1)\n",
    "    else:\n",
    "        group['stability'] = 0.0\n",
    "    group['avg_retention'] = round(sum(group['retention'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 3)\n",
    "    group['avg_interval'] = round(sum(group['delta_t'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 1)\n",
    "    del group['total_cnt']\n",
    "    del group['retention']\n",
    "    del group['delta_t']\n",
    "    return group\n",
    "\n",
    "df = df.groupby(by=['r_history'], group_keys=False).progress_apply(cal_stability)\n",
    "print(\"Stability calculated.\")\n",
    "df.reset_index(drop = True, inplace = True)\n",
    "df.drop_duplicates(inplace=True)\n",
    "df.sort_values(by=['r_history'], inplace=True, ignore_index=True)\n",
    "\n",
    "if df.shape[0] > 0:\n",
    "    for idx in tqdm(df.index, desc=\"analysis\"):\n",
    "        item = df.loc[idx]\n",
    "        index = df[(df['i'] == item['i'] + 1) & (df['r_history'].str.startswith(item['r_history']))].index\n",
    "        df.loc[index, 'last_stability'] = item['stability']\n",
    "    df['factor'] = round(df['stability'] / df['last_stability'], 2)\n",
    "    df = df[(df['i'] >= 2) & (df['group_cnt'] >= 100)].copy()\n",
    "    df['last_recall'] = df['r_history'].map(lambda x: x[-1])\n",
    "    df = df[df.groupby(['i', 'r_history'], group_keys=False)['group_cnt'].transform(max) == df['group_cnt']]\n",
    "    df.to_csv('./stability_for_analysis.tsv', sep='\\t', index=None)\n",
    "    print(\"Analysis saved!\")\n",
    "    caption = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "    analysis = df[df['r_history'].str.contains(r'^[1-4][^124]*$', regex=True)][['r_history', 'avg_interval', 'avg_retention', 'stability', 'factor', 'group_cnt']].to_string(index=False)\n",
    "    print(caption + analysis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "init_w = [1, 1, 5, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2, -0.2, 0.2, 1, 0.8, 1.2]\n",
    "\n",
    "class FSRS(nn.Module):\n",
    "    def __init__(self, w: List[float]):\n",
    "        super(FSRS, self).__init__()\n",
    "        self.w = nn.Parameter(torch.tensor(w, dtype=torch.float32))\n",
    "\n",
    "    def stability_after_success(self, state: Tensor, new_d: Tensor, r: Tensor) -> Tensor:\n",
    "        new_s = state[:,0] * (1 + torch.exp(self.w[6]) *\n",
    "                        (11 - new_d) *\n",
    "                        torch.pow(state[:,0], self.w[7]) *\n",
    "                        (torch.exp((1 - r) * self.w[8]) - 1))\n",
    "        return new_s\n",
    "\n",
    "    def stability_after_failure(self, state: Tensor, new_d: Tensor, r: Tensor) -> Tensor:\n",
    "        new_s = self.w[9] * torch.pow(new_d, self.w[10]) * torch.pow(\n",
    "            state[:,0], self.w[11]) * torch.exp((1 - r) * self.w[12])\n",
    "        return new_s\n",
    "\n",
    "    def step(self, X: Tensor, state: Tensor) -> Tensor:\n",
    "        '''\n",
    "        :param X: shape[batch_size, 2], X[:,0] is elapsed time, X[:,1] is rating\n",
    "        :param state: shape[batch_size, 2], state[:,0] is stability, state[:,1] is difficulty\n",
    "        :return state:\n",
    "        '''\n",
    "        if torch.equal(state, torch.zeros_like(state)):\n",
    "            # first learn, init memory states\n",
    "            new_s = self.w[0] + self.w[1] * (X[:,1] - 1)\n",
    "            new_d = self.w[2] + self.w[3] * (X[:,1] - 3)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "        else:\n",
    "            r = torch.exp(np.log(0.9) * X[:,0] / state[:,0])\n",
    "            new_d = state[:,1] + self.w[4] * (X[:,1] - 3)\n",
    "            new_d = self.mean_reversion(self.w[2], new_d)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "            condition = X[:,1] > 1\n",
    "            new_s = torch.where(condition, self.stability_after_success(state, new_d, r), self.stability_after_failure(state, new_d, r))\n",
    "            new_s = torch.where(X[:,1] == 2, new_s * self.w[13], new_s)\n",
    "            new_s = torch.where(X[:,1] == 4, new_s * self.w[14], new_s)\n",
    "        new_s = new_s.clamp(0.1, 36500)\n",
    "        return torch.stack([new_s, new_d], dim=1)\n",
    "\n",
    "    def forward(self, inputs: Tensor, state: Optional[Tensor]=None) -> Tensor:\n",
    "        '''\n",
    "        :param inputs: shape[seq_len, batch_size, 2]\n",
    "        '''\n",
    "        if state is None:\n",
    "            state = torch.zeros((inputs.shape[1], 2))\n",
    "        outputs = []\n",
    "        for X in inputs:\n",
    "            state = self.step(X, state)\n",
    "            outputs.append(state)\n",
    "        return torch.stack(outputs), state\n",
    "\n",
    "    def mean_reversion(self, init: Tensor, current: Tensor) -> Tensor:\n",
    "        return self.w[5] * init + (1-self.w[5]) * current\n",
    "\n",
    "class WeightClipper:\n",
    "    def __init__(self, frequency: int=1):\n",
    "        self.frequency = frequency\n",
    "\n",
    "    def __call__(self, module):\n",
    "        if hasattr(module, 'w'):\n",
    "            w = module.w.data\n",
    "            w[0] = w[0].clamp(0.1, 10)\n",
    "            w[1] = w[1].clamp(0.1, 5)\n",
    "            w[2] = w[2].clamp(1, 10)\n",
    "            w[3] = w[3].clamp(-5, -0.1)\n",
    "            w[4] = w[4].clamp(-5, -0.1)\n",
    "            w[5] = w[5].clamp(0.05, 0.5)\n",
    "            w[6] = w[6].clamp(0, 2)\n",
    "            w[7] = w[7].clamp(-0.8, -0.15)\n",
    "            w[8] = w[8].clamp(0.01, 1.5)\n",
    "            w[9] = w[9].clamp(0.5, 5)\n",
    "            w[10] = w[10].clamp(-2, -0.01)\n",
    "            w[11] = w[11].clamp(0.01, 0.9)\n",
    "            w[12] = w[12].clamp(0.01, 2)\n",
    "            w[13] = w[13].clamp(0.1, 1)\n",
    "            w[14] = w[14].clamp(1, 2)\n",
    "            module.w.data = w\n",
    "\n",
    "def lineToTensor(line: str) -> Tensor:\n",
    "    ivl = line[0].split(',')\n",
    "    response = line[1].split(',')\n",
    "    tensor = torch.zeros(len(response), 2)\n",
    "    for li, response in enumerate(response):\n",
    "        tensor[li][0] = int(ivl[li])\n",
    "        tensor[li][1] = int(response)\n",
    "    return tensor\n",
    "\n",
    "class RevlogDataset(Dataset):\n",
    "    def __init__(self, dataframe: pd.DataFrame):\n",
    "        if dataframe.empty:\n",
    "            raise ValueError('Training data is inadequate.')\n",
    "        padded = pad_sequence(dataframe['tensor'].to_list(), batch_first=True, padding_value=0)\n",
    "        self.x_train = padded.int()\n",
    "        self.t_train = torch.tensor(dataframe['delta_t'].values, dtype=torch.int)\n",
    "        self.y_train = torch.tensor(dataframe['y'].values, dtype=torch.float)\n",
    "        self.seq_len = torch.tensor(dataframe['tensor'].map(len).values, dtype=torch.long)\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        return self.x_train[idx], self.t_train[idx], self.y_train[idx], self.seq_len[idx]\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.y_train)\n",
    "\n",
    "class RevlogSampler(Sampler[List[int]]):\n",
    "    def __init__(self, data_source: RevlogDataset, batch_size: int):\n",
    "        self.data_source = data_source\n",
    "        self.batch_size = batch_size\n",
    "        lengths = np.array(data_source.seq_len)\n",
    "        indices = np.argsort(lengths)\n",
    "        full_batches, remainder = divmod(indices.size, self.batch_size)\n",
    "        if full_batches > 0:\n",
    "            if remainder == 0:\n",
    "                self.batch_indices = np.split(indices, full_batches)\n",
    "            else:\n",
    "                self.batch_indices = np.split(indices[:-remainder], full_batches)\n",
    "        else:\n",
    "            self.batch_indices = []\n",
    "        if remainder > 0:\n",
    "            self.batch_indices.append(indices[-remainder:])\n",
    "        self.batch_nums = len(self.batch_indices)\n",
    "        # seed = int(torch.empty((), dtype=torch.int64).random_().item())\n",
    "        seed = 2023\n",
    "        self.generator = torch.Generator()\n",
    "        self.generator.manual_seed(seed)\n",
    "\n",
    "    def __iter__(self):\n",
    "        yield from (self.batch_indices[idx] for idx in torch.randperm(self.batch_nums, generator=self.generator).tolist())\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.data_source)\n",
    "\n",
    "\n",
    "def collate_fn(batch):\n",
    "    sequences, delta_ts, labels, seq_lens = zip(*batch)\n",
    "    sequences_packed = pack_padded_sequence(torch.stack(sequences, dim=1), lengths=torch.stack(seq_lens), batch_first=False, enforce_sorted=False)\n",
    "    sequences_padded, length = pad_packed_sequence(sequences_packed, batch_first=False)\n",
    "    sequences_padded = torch.as_tensor(sequences_padded)\n",
    "    seq_lens = torch.as_tensor(length)\n",
    "    delta_ts = torch.as_tensor(delta_ts)\n",
    "    labels = torch.as_tensor(labels)\n",
    "    return sequences_padded, delta_ts, labels, seq_lens\n",
    "\n",
    "class Trainer:\n",
    "    def __init__(self, train_set: pd.DataFrame, test_set: pd.DataFrame, init_w: List[float], n_epoch: int=1, lr: float=1e-2, batch_size: int=256) -> None:\n",
    "        self.model = FSRS(init_w)\n",
    "        self.optimizer = torch.optim.Adam(self.model.parameters(), lr=lr)\n",
    "        self.clipper = WeightClipper()\n",
    "        self.batch_size = batch_size\n",
    "        self.build_dataset(train_set, test_set)\n",
    "        self.n_epoch = n_epoch\n",
    "        self.batch_nums = self.next_train_data_loader.batch_sampler.batch_nums\n",
    "        self.scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(self.optimizer, T_max=self.batch_nums * n_epoch)\n",
    "        self.avg_train_losses = []\n",
    "        self.avg_eval_losses = []\n",
    "        self.loss_fn = nn.BCELoss(reduction='sum')\n",
    "\n",
    "    def build_dataset(self, train_set: pd.DataFrame, test_set: pd.DataFrame):\n",
    "        pre_train_set = train_set[train_set['i'] == 2]\n",
    "        self.pre_train_set = RevlogDataset(pre_train_set)\n",
    "        sampler = RevlogSampler(self.pre_train_set, batch_size=self.batch_size)\n",
    "        self.pre_train_data_loader = DataLoader(self.pre_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        next_train_set = train_set[train_set['i'] > 2]\n",
    "        self.next_train_set = RevlogDataset(next_train_set)\n",
    "        sampler = RevlogSampler(self.next_train_set, batch_size=self.batch_size)\n",
    "        self.next_train_data_loader = DataLoader(self.next_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.train_set = RevlogDataset(train_set)\n",
    "        sampler = RevlogSampler(self.train_set, batch_size=self.batch_size)\n",
    "        self.train_data_loader = DataLoader(self.train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.test_set = RevlogDataset(test_set)\n",
    "        sampler = RevlogSampler(self.test_set, batch_size=self.batch_size)\n",
    "        self.test_data_loader = DataLoader(self.test_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "        print(\"dataset built\")\n",
    "\n",
    "    def train(self, verbose: bool=True):\n",
    "        # pretrain\n",
    "        best_loss = np.inf\n",
    "        weighted_loss, w = self.eval()\n",
    "        if weighted_loss < best_loss:\n",
    "            best_loss = weighted_loss\n",
    "            best_w = w\n",
    "\n",
    "        pbar = tqdm(desc=\"pre-train\", colour=\"red\", total=len(self.pre_train_data_loader) * self.n_epoch)\n",
    "        for k in range(self.n_epoch):\n",
    "            for i, batch in enumerate(self.pre_train_data_loader):\n",
    "                self.model.train()\n",
    "                self.optimizer.zero_grad()\n",
    "                sequences, delta_ts, labels, seq_lens = batch\n",
    "                real_batch_size = seq_lens.shape[0]\n",
    "                outputs, _ = self.model(sequences)\n",
    "                stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "                retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "                loss = self.loss_fn(retentions, labels)\n",
    "                loss.backward()\n",
    "                self.optimizer.step()\n",
    "                self.model.apply(self.clipper)\n",
    "                pbar.update(n=real_batch_size)\n",
    "\n",
    "        pbar.close()\n",
    "        for name, param in self.model.named_parameters():\n",
    "            tqdm.write(f\"{name}: {list(map(lambda x: round(float(x), 4),param))}\")\n",
    "\n",
    "        epoch_len = len(self.next_train_data_loader)\n",
    "        pbar = tqdm(desc=\"train\", colour=\"red\", total=epoch_len*self.n_epoch)\n",
    "        print_len = max(self.batch_nums*self.n_epoch // 10, 1)\n",
    "        for k in range(self.n_epoch):\n",
    "            weighted_loss, w = self.eval()\n",
    "            if weighted_loss < best_loss:\n",
    "                best_loss = weighted_loss\n",
    "                best_w = w\n",
    "\n",
    "            for i, batch in enumerate(self.next_train_data_loader):\n",
    "                self.model.train()\n",
    "                self.optimizer.zero_grad()\n",
    "                sequences, delta_ts, labels, seq_lens = batch\n",
    "                real_batch_size = seq_lens.shape[0]\n",
    "                outputs, _ = self.model(sequences)\n",
    "                stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "                retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "                loss = self.loss_fn(retentions, labels)\n",
    "                loss.backward()\n",
    "                for param in self.model.parameters():\n",
    "                    param.grad[:2] = torch.zeros(2)\n",
    "                self.optimizer.step()\n",
    "                self.scheduler.step()\n",
    "                self.model.apply(self.clipper)\n",
    "                pbar.update(real_batch_size)\n",
    "\n",
    "                if verbose and (k * self.batch_nums + i + 1) % print_len == 0:\n",
    "                    tqdm.write(f\"iteration: {k * epoch_len + (i + 1) * self.batch_size}\")\n",
    "                    for name, param in self.model.named_parameters():\n",
    "                        tqdm.write(f\"{name}: {list(map(lambda x: round(float(x), 4),param))}\")\n",
    "        pbar.close()\n",
    "\n",
    "        weighted_loss, w = self.eval()\n",
    "        if weighted_loss < best_loss:\n",
    "            best_loss = weighted_loss\n",
    "            best_w = w\n",
    "\n",
    "        return best_w\n",
    "\n",
    "    def eval(self):\n",
    "        self.model.eval()\n",
    "        with torch.no_grad():\n",
    "            sequences, delta_ts, labels, seq_lens = self.train_set.x_train, self.train_set.t_train, self.train_set.y_train, self.train_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "            tran_loss = self.loss_fn(retentions, labels)/len(self.train_set)\n",
    "            self.avg_train_losses.append(tran_loss)\n",
    "            tqdm.write(f\"Loss in trainset: {tran_loss:.4f}\")\n",
    "\n",
    "            sequences, delta_ts, labels, seq_lens = self.test_set.x_train, self.test_set.t_train, self.test_set.y_train, self.test_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "            test_loss = self.loss_fn(retentions, labels)/len(self.test_set)\n",
    "            self.avg_eval_losses.append(test_loss)\n",
    "            tqdm.write(f\"Loss in testset: {test_loss:.4f}\")\n",
    "\n",
    "            w = list(map(lambda x: round(float(x), 4), dict(self.model.named_parameters())['w'].data))\n",
    "\n",
    "            weighted_loss = (tran_loss * len(self.train_set) + test_loss * len(self.test_set)) / (len(self.train_set) + len(self.test_set))\n",
    "\n",
    "            return weighted_loss, w\n",
    "\n",
    "    def plot(self):\n",
    "        fig = plt.figure()\n",
    "        ax = fig.gca()\n",
    "        ax.plot(self.avg_train_losses, label='train')\n",
    "        ax.plot(self.avg_eval_losses, label='test')\n",
    "        ax.set_xlabel('epoch')\n",
    "        ax.set_ylabel('loss')\n",
    "        ax.legend()\n",
    "        return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f661f27fe7bb4bb6b236743669372c43",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/88151 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensorized!\n",
      "TRAIN: 57372 TEST: 30779\n",
      "dataset built\n",
      "Loss in trainset: 0.3310\n",
      "Loss in testset: 0.3099\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "00f18f9bd397425dbae9a50fe9ff4ea9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/15276 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [1.2588, 1.8518, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0, 0.8, 1.2]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0a019bb484aa41e69ccc5c8b95601f25",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156840 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3285\n",
      "Loss in testset: 0.3076\n",
      "iteration: 15360\n",
      "w: [1.2327, 2.0554, 5.0945, -1.2188, -0.9676, 0.05, 1.5585, -0.15, 0.9657, 2.0815, -0.1375, 0.3451, 0.9194, 0.4731, 1.7175]\n",
      "iteration: 30720\n",
      "w: [1.2313, 2.0664, 5.2177, -1.7147, -1.1497, 0.05, 1.6023, -0.15, 1.009, 2.0744, -0.1602, 0.2618, 0.8875, 0.4172, 1.715]\n",
      "iteration: 46080\n",
      "w: [1.2312, 2.067, 5.2014, -1.7334, -1.2308, 0.05, 1.5928, -0.1941, 1.0035, 2.0806, -0.1688, 0.3148, 0.8801, 0.4467, 1.8924]\n",
      "Loss in trainset: 0.3130\n",
      "Loss in testset: 0.2943\n",
      "iteration: 60984\n",
      "w: [1.2312, 2.067, 5.2562, -1.877, -1.2647, 0.05, 1.5579, -0.2418, 0.9674, 2.0331, -0.2217, 0.3214, 0.8694, 0.4225, 1.8399]\n",
      "iteration: 76344\n",
      "w: [1.2312, 2.067, 5.1482, -1.8348, -1.2223, 0.05, 1.6224, -0.2006, 1.0207, 2.0349, -0.2188, 0.2465, 0.8302, 0.4283, 1.7742]\n",
      "iteration: 91704\n",
      "w: [1.2312, 2.067, 5.2146, -1.8894, -1.282, 0.05, 1.5986, -0.2551, 0.9987, 2.0877, -0.1716, 0.2796, 0.7996, 0.3895, 1.863]\n",
      "Loss in trainset: 0.3126\n",
      "Loss in testset: 0.2940\n",
      "iteration: 106608\n",
      "w: [1.2312, 2.067, 5.1592, -1.8455, -1.2541, 0.05, 1.6212, -0.2405, 1.015, 2.0426, -0.2205, 0.3158, 0.6948, 0.4141, 1.8121]\n",
      "iteration: 121968\n",
      "w: [1.2312, 2.067, 5.161, -1.8339, -1.2709, 0.05, 1.6171, -0.2387, 1.0088, 2.0659, -0.1971, 0.3368, 0.6784, 0.4391, 1.8051]\n",
      "iteration: 137328\n",
      "w: [1.2312, 2.067, 5.1625, -1.8475, -1.2751, 0.05, 1.6177, -0.2301, 1.0073, 2.0588, -0.2046, 0.3415, 0.6703, 0.4192, 1.7976]\n",
      "iteration: 152688\n",
      "w: [1.2312, 2.067, 5.165, -1.8469, -1.2778, 0.05, 1.6125, -0.2361, 1.0022, 2.0543, -0.2091, 0.3371, 0.6665, 0.4162, 1.7919]\n",
      "Loss in trainset: 0.3125\n",
      "Loss in testset: 0.2939\n",
      "TRAIN: 59696 TEST: 28455\n",
      "dataset built\n",
      "Loss in trainset: 0.3174\n",
      "Loss in testset: 0.3367\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7b032fe12c6947b6a2ca8c3a9f2d11b9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/22374 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [2.0143, 2.047, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0, 0.8, 1.2]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7a0d11893131402cb865c720a9593296",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156714 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3144\n",
      "Loss in testset: 0.3350\n",
      "iteration: 15360\n",
      "w: [2.1098, 2.1547, 5.0366, -1.1451, -0.9467, 0.0598, 1.5625, -0.15, 0.9906, 2.0556, -0.1738, 0.1993, 1.1691, 0.4987, 1.8178]\n",
      "iteration: 30720\n",
      "w: [2.1147, 2.1603, 5.1643, -1.6703, -1.1539, 0.05, 1.554, -0.1805, 1.012, 2.0299, -0.2199, 0.3438, 1.0519, 0.5854, 1.718]\n",
      "iteration: 46080\n",
      "w: [2.1149, 2.1605, 5.1079, -1.9176, -1.0906, 0.05, 1.5336, -0.1831, 1.0044, 1.9894, -0.2698, 0.3193, 0.8926, 0.4149, 1.7914]\n",
      "Loss in trainset: 0.3000\n",
      "Loss in testset: 0.3200\n",
      "iteration: 60942\n",
      "w: [2.1149, 2.1605, 5.1013, -1.8289, -1.1109, 0.0594, 1.4759, -0.2241, 0.9533, 2.0309, -0.2348, 0.331, 0.8808, 0.4427, 1.7374]\n",
      "iteration: 76302\n",
      "w: [2.1149, 2.1605, 5.1078, -1.8671, -1.1273, 0.05, 1.4568, -0.2348, 0.9398, 2.0199, -0.2473, 0.3661, 0.7661, 0.4513, 1.6206]\n",
      "iteration: 91662\n",
      "w: [2.1149, 2.1605, 5.032, -1.7906, -1.1377, 0.05, 1.5049, -0.1795, 0.9808, 2.0086, -0.2606, 0.3436, 0.7189, 0.4367, 1.6337]\n",
      "Loss in trainset: 0.2996\n",
      "Loss in testset: 0.3196\n",
      "iteration: 106524\n",
      "w: [2.1149, 2.1605, 5.0536, -1.7837, -1.1837, 0.05, 1.4929, -0.2045, 0.9636, 2.0384, -0.2282, 0.3619, 0.7211, 0.4282, 1.6148]\n",
      "iteration: 121884\n",
      "w: [2.1149, 2.1605, 5.0486, -1.7906, -1.1838, 0.05, 1.5027, -0.1945, 0.9708, 2.0424, -0.2232, 0.3546, 0.6913, 0.4456, 1.6169]\n",
      "iteration: 137244\n",
      "w: [2.1149, 2.1605, 5.0637, -1.8078, -1.1939, 0.05, 1.4926, -0.2013, 0.9598, 2.0486, -0.2166, 0.3599, 0.6922, 0.4296, 1.5942]\n",
      "iteration: 152604\n",
      "w: [2.1149, 2.1605, 5.0623, -1.8056, -1.1933, 0.05, 1.4922, -0.2031, 0.959, 2.0461, -0.2189, 0.3576, 0.6889, 0.4316, 1.5935]\n",
      "Loss in trainset: 0.2996\n",
      "Loss in testset: 0.3195\n",
      "TRAIN: 59234 TEST: 28917\n",
      "dataset built\n",
      "Loss in trainset: 0.3228\n",
      "Loss in testset: 0.3255\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "054a932b696f4be8a3ff5a6d5664f21d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/20916 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [1.2804, 1.8287, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0, 0.8, 1.2]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f1521268b06b4fe1805dfd7f8be57d32",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156786 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3205\n",
      "Loss in testset: 0.3227\n",
      "iteration: 15360\n",
      "w: [1.2103, 1.9125, 5.163, -1.3954, -1.1032, 0.05, 1.5538, -0.1733, 0.9908, 2.0436, -0.146, 0.3142, 1.1292, 0.4864, 1.6018]\n",
      "iteration: 30720\n",
      "w: [1.2066, 1.9168, 5.2041, -1.6459, -1.1762, 0.05, 1.5107, -0.2074, 0.9688, 1.9295, -0.2669, 0.3125, 0.6635, 0.4763, 1.447]\n",
      "iteration: 46080\n",
      "w: [1.2065, 1.917, 5.1065, -1.6626, -1.1095, 0.05, 1.5405, -0.1982, 0.9873, 1.9864, -0.2166, 0.328, 0.5287, 0.48, 1.5757]\n",
      "Loss in trainset: 0.3060\n",
      "Loss in testset: 0.3071\n",
      "iteration: 60966\n",
      "w: [1.2065, 1.917, 5.105, -1.6456, -1.2425, 0.05, 1.5206, -0.2007, 0.959, 2.051, -0.1632, 0.37, 0.4505, 0.4016, 1.7425]\n",
      "iteration: 76326\n",
      "w: [1.2065, 1.917, 5.0827, -1.6328, -1.2617, 0.05, 1.5069, -0.2229, 0.9412, 2.034, -0.1799, 0.3224, 0.3986, 0.4175, 1.6699]\n",
      "iteration: 91686\n",
      "w: [1.2065, 1.917, 5.0549, -1.6867, -1.2567, 0.05, 1.5551, -0.17, 0.9808, 2.0594, -0.1486, 0.3288, 0.3607, 0.4162, 1.5832]\n",
      "Loss in trainset: 0.3058\n",
      "Loss in testset: 0.3069\n",
      "iteration: 106572\n",
      "w: [1.2065, 1.917, 5.0579, -1.7314, -1.2484, 0.0515, 1.5597, -0.1868, 0.9825, 2.0384, -0.169, 0.3192, 0.2917, 0.4681, 1.553]\n",
      "iteration: 121932\n",
      "w: [1.2065, 1.917, 5.0607, -1.7467, -1.262, 0.05, 1.5462, -0.2086, 0.9673, 2.0358, -0.1707, 0.332, 0.2599, 0.4199, 1.5013]\n",
      "iteration: 137292\n",
      "w: [1.2065, 1.917, 5.0758, -1.7665, -1.2745, 0.05, 1.5387, -0.2131, 0.9591, 2.0428, -0.1629, 0.3396, 0.2553, 0.4174, 1.5031]\n",
      "iteration: 152652\n",
      "w: [1.2065, 1.917, 5.0744, -1.7649, -1.2743, 0.05, 1.5382, -0.2133, 0.9583, 2.0419, -0.1639, 0.34, 0.2553, 0.4169, 1.5034]\n",
      "Loss in trainset: 0.3057\n",
      "Loss in testset: 0.3069\n",
      "\n",
      "Training finished!\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lr: float = 4e-2\n",
    "n_epoch: int = 3\n",
    "n_splits: int = 3\n",
    "batch_size: int = 512\n",
    "verbose: bool = True\n",
    "\n",
    "dataset = pd.read_csv(\"./revlog_history.tsv\", sep='\\t', index_col=None, dtype={'r_history': str ,'t_history': str} )\n",
    "dataset = dataset[(dataset['i'] > 1) & (dataset['delta_t'] > 0) & (dataset['t_history'].str.count(',0') == 0)]\n",
    "if dataset.empty:\n",
    "    raise ValueError('Training data is inadequate.')\n",
    "dataset['tensor'] = dataset.progress_apply(lambda x: lineToTensor(list(zip([x['t_history']], [x['r_history']]))[0]), axis=1)\n",
    "dataset['group'] = dataset['r_history'] + dataset['t_history']\n",
    "print(\"Tensorized!\")\n",
    "\n",
    "n_pre_train_groups = len(dataset[dataset['i'] == 2]['group'].unique())\n",
    "if n_pre_train_groups < n_splits:\n",
    "    print(\"Not enough groups for pre-training. Splitting into {} folds.\".format(n_pre_train_groups))\n",
    "    n_splits = n_pre_train_groups\n",
    "\n",
    "w = []\n",
    "plots = []\n",
    "if n_splits > 1:\n",
    "    sgkf = StratifiedGroupKFold(n_splits=n_splits)\n",
    "    for train_index, test_index in sgkf.split(dataset, dataset['i'], dataset['group']):\n",
    "        print(\"TRAIN:\", len(train_index), \"TEST:\",  len(test_index))\n",
    "        train_set = dataset.iloc[train_index].copy()\n",
    "        test_set = dataset.iloc[test_index].copy()\n",
    "        trainer = Trainer(train_set, test_set, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "        w.append(trainer.train(verbose=verbose))\n",
    "        plots.append(trainer.plot())\n",
    "else:\n",
    "    trainer = Trainer(dataset, dataset, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "    w.append(trainer.train(verbose=verbose))\n",
    "    plots.append(trainer.plot())\n",
    "\n",
    "w = np.array(w)\n",
    "avg_w = np.round(np.mean(w, axis=0), 4)\n",
    "w = avg_w.tolist()\n",
    "print(\"\\nTraining finished!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1.5175, 2.0482, 5.1005, -1.8058, -1.2485, 0.05, 1.5477, -0.2175, 0.9732, 2.0474, -0.1974, 0.3448, 0.5368, 0.4216, 1.6296]\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "\n",
      "first rating: 1\n",
      "rating history: 1,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,2d,4d,8d,14d,26d,1.5m,2.5m,4.1m,6.5m,10.1m\n",
      "difficulty history: 0,8.7,8.5,8.4,8.2,8.0,7.9,7.8,7.6,7.5,7.4\n",
      "\n",
      "first rating: 2\n",
      "rating history: 2,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,4d,10d,22d,1.5m,2.9m,5.3m,9.2m,1.3y,2.0y,3.1y\n",
      "difficulty history: 0,6.9,6.8,6.7,6.6,6.6,6.5,6.4,6.4,6.3,6.2\n",
      "\n",
      "first rating: 3\n",
      "rating history: 3,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,6d,17d,1.4m,3.2m,6.6m,1.0y,1.8y,3.1y,5.0y,7.8y\n",
      "difficulty history: 0,5.1,5.1,5.1,5.1,5.1,5.1,5.1,5.1,5.1,5.1\n",
      "\n",
      "first rating: 4\n",
      "rating history: 4,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,8d,26d,2.4m,5.8m,1.0y,2.0y,3.7y,6.4y,10.4y,16.2y\n",
      "difficulty history: 0,3.3,3.4,3.5,3.6,3.6,3.7,3.8,3.8,3.9,4.0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(w)\n",
    "\n",
    "class Collection:\n",
    "    def __init__(self, w: List[float]) -> None:\n",
    "        self.model = FSRS(w)\n",
    "        self.model.eval()\n",
    "\n",
    "    def predict(self, t_history: str, r_history: str):\n",
    "        with torch.no_grad():\n",
    "            line_tensor = lineToTensor(list(zip([t_history], [r_history]))[0]).unsqueeze(1)\n",
    "            output_t = self.model(line_tensor)\n",
    "            return output_t[-1][0]\n",
    "\n",
    "    def batch_predict(self, dataset):\n",
    "        fast_dataset = RevlogDataset(dataset)\n",
    "        with torch.no_grad():\n",
    "            outputs, _ = self.model(fast_dataset.x_train.transpose(0, 1))\n",
    "            stabilities, difficulties = outputs[fast_dataset.seq_len-1, torch.arange(len(fast_dataset))].transpose(0, 1)\n",
    "            return stabilities.tolist(), difficulties.tolist()\n",
    "        \n",
    "requestRetention = 0.9\n",
    "\n",
    "my_collection = Collection(w)\n",
    "preview_text = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "for first_rating in (1,2,3,4):\n",
    "    preview_text += f'\\nfirst rating: {first_rating}\\n'\n",
    "    t_history = \"0\"\n",
    "    d_history = \"0\"\n",
    "    r_history = f\"{first_rating}\"  # the first rating of the new card\n",
    "    # print(\"stability, difficulty, lapses\")\n",
    "    for i in range(10):\n",
    "        states = my_collection.predict(t_history, r_history)\n",
    "        # print('{0:9.2f} {1:11.2f} {2:7.0f}'.format(\n",
    "            # *list(map(lambda x: round(float(x), 4), states))))\n",
    "        next_t = max(round(float(np.log(requestRetention)/np.log(0.9) * states[0])), 1)\n",
    "        difficulty = round(float(states[1]), 1)\n",
    "        t_history += f',{int(next_t)}'\n",
    "        d_history += f',{difficulty}'\n",
    "        r_history += f\",3\"\n",
    "    preview_text += f\"rating history: {r_history}\\n\"\n",
    "    preview_text += \"interval history: \" + \",\".join([f\"{ivl}d\" if ivl < 30 else f\"{ivl / 30:.1f}m\" if ivl < 365 else f\"{ivl / 365:.1f}y\" for ivl in map(int, t_history.split(','))]) + \"\\n\"\n",
    "    preview_text += f\"difficulty history: {d_history}\\n\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([5.6139, 5.1005])\n",
      "tensor([17.2959,  5.1005])\n",
      "tensor([43.2204,  5.1005])\n",
      "tensor([96.9478,  5.1005])\n",
      "tensor([198.6142,   5.1005])\n",
      "tensor([9.0051, 7.4726])\n",
      "tensor([2.9416, 9.7262])\n",
      "tensor([4.6571, 9.4949])\n",
      "tensor([7.6213, 9.2752])\n",
      "tensor([12.3984,  9.0665])\n",
      "tensor([19.5082,  8.8682])\n",
      "tensor([31.1911,  8.6798])\n",
      "rating history: 3,3,3,3,3,1,1,3,3,3,3,3\n",
      "interval history: 0,6,17,43,97,199,9,3,5,8,12,20,31\n",
      "difficulty history: 0,5.1,5.1,5.1,5.1,5.1,7.5,9.7,9.5,9.3,9.1,8.9,8.7\n"
     ]
    }
   ],
   "source": [
    "test_rating_sequence = \"3,3,3,3,3,1,1,3,3,3,3,3\"\n",
    "requestRetention = 0.9  # recommended setting: 0.8 ~ 0.9\n",
    "easyBonus = 1.3\n",
    "hardInterval = 1.2\n",
    "\n",
    "t_history = \"0\"\n",
    "d_history = \"0\"\n",
    "for i in range(len(test_rating_sequence.split(','))):\n",
    "    rating = test_rating_sequence[2*i]\n",
    "    last_t = int(t_history.split(',')[-1])\n",
    "    r_history = test_rating_sequence[:2*i+1]\n",
    "    states = my_collection.predict(t_history, r_history)\n",
    "    print(states)\n",
    "    next_t = max(1,round(float(np.log(requestRetention)/np.log(0.9) * states[0])))\n",
    "    if rating == '4':\n",
    "        next_t = round(next_t * easyBonus)\n",
    "    elif rating == '2':\n",
    "        next_t = round(last_t * hardInterval)\n",
    "    t_history += f',{int(next_t)}'\n",
    "    difficulty = round(float(states[1]), 1)\n",
    "    d_history += f',{difficulty}'\n",
    "preview_text = f\"rating history: {test_rating_sequence}\\n\"\n",
    "preview_text += f\"interval history: {t_history}\\n\"\n",
    "preview_text += f\"difficulty history: {d_history}\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss before: 0.3237, loss after: 0.3059, improvement: 0.0177\n"
     ]
    }
   ],
   "source": [
    "my_collection = Collection(init_w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset['p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_before = dataset['log_loss'].mean()\n",
    "\n",
    "my_collection = Collection(w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset['p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_after = dataset['log_loss'].mean()\n",
    "\n",
    "tmp = dataset.copy()\n",
    "tmp['stability'] = tmp['stability'].map(lambda x: round(x, 2))\n",
    "tmp['difficulty'] = tmp['difficulty'].map(lambda x: round(x, 2))\n",
    "tmp['p'] = tmp['p'].map(lambda x: round(x, 2))\n",
    "tmp['log_loss'] = tmp['log_loss'].map(lambda x: round(x, 2))\n",
    "tmp.rename(columns={\"r\": \"grade\", \"p\": \"retrievability\"}, inplace=True)\n",
    "tmp[['id', 'cid', 'review_date', 'r_history', 't_history', 'delta_t', 'grade', 'stability', 'difficulty', 'retrievability', 'log_loss']].to_csv(\"./evaluation.tsv\", sep='\\t', index=False)\n",
    "del tmp\n",
    "print(f\"loss before: {loss_before:.4f}, loss after: {loss_after:.4f}, improvement: {loss_before - loss_after:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R-squared: 0.9408\n",
      "RMSE: 0.0183\n",
      "[0.04604873 0.95009159]\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Last rating: 1\n",
      "R-squared: 0.2593\n",
      "RMSE: 0.0488\n",
      "[0.31850143 0.62465181]\n",
      "\n",
      "Last rating: 2\n",
      "R-squared: 0.7863\n",
      "RMSE: 0.0334\n",
      "[0.20333066 0.74917427]\n",
      "\n",
      "Last rating: 3\n",
      "R-squared: 0.9432\n",
      "RMSE: 0.0186\n",
      "[-0.02696748  1.03678789]\n",
      "\n",
      "Last rating: 4\n",
      "R-squared: 0.3527\n",
      "RMSE: 0.0249\n",
      "[0.30627392 0.68729765]\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1600x1200 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# code from https://github.com/papousek/duolingo-halflife-regression/blob/master/evaluation.py\n",
    "def load_brier(predictions, real, bins=20):\n",
    "    counts = np.zeros(bins)\n",
    "    correct = np.zeros(bins)\n",
    "    prediction = np.zeros(bins)\n",
    "    for p, r in zip(predictions, real):\n",
    "        bin = min(int(p * bins), bins - 1)\n",
    "        counts[bin] += 1\n",
    "        correct[bin] += r\n",
    "        prediction[bin] += p\n",
    "    np.seterr(invalid='ignore')\n",
    "    prediction_means = prediction / counts\n",
    "    prediction_means[np.isnan(prediction_means)] = ((np.arange(bins) + 0.5) / bins)[np.isnan(prediction_means)]\n",
    "    correct_means = correct / counts\n",
    "    correct_means[np.isnan(correct_means)] = 0\n",
    "    size = len(predictions)\n",
    "    answer_mean = sum(correct) / size\n",
    "    return {\n",
    "        \"reliability\": sum(counts * (correct_means - prediction_means) ** 2) / size,\n",
    "        \"resolution\": sum(counts * (correct_means - answer_mean) ** 2) / size,\n",
    "        \"uncertainty\": answer_mean * (1 - answer_mean),\n",
    "        \"detail\": {\n",
    "            \"bin_count\": bins,\n",
    "            \"bin_counts\": list(counts),\n",
    "            \"bin_prediction_means\": list(prediction_means),\n",
    "            \"bin_correct_means\": list(correct_means),\n",
    "        }\n",
    "    }\n",
    "\n",
    "\n",
    "def plot_brier(predictions, real, bins=20):\n",
    "    brier = load_brier(predictions, real, bins=bins)\n",
    "    bin_prediction_means = brier['detail']['bin_prediction_means']\n",
    "    bin_correct_means = brier['detail']['bin_correct_means']\n",
    "    bin_counts = brier['detail']['bin_counts']\n",
    "    r2 = r2_score(bin_correct_means, bin_prediction_means, sample_weight=bin_counts)\n",
    "    rmse = mean_squared_error(bin_correct_means, bin_prediction_means, sample_weight=bin_counts, squared=False)\n",
    "    print(f\"R-squared: {r2:.4f}\")\n",
    "    print(f\"RMSE: {rmse:.4f}\")\n",
    "    ax = plt.gca()\n",
    "    ax.set_xlim([0, 1])\n",
    "    ax.set_ylim([0, 1])\n",
    "    plt.grid(True)\n",
    "    fit_wls = sm.WLS(bin_correct_means, sm.add_constant(bin_prediction_means), weights=bin_counts).fit()\n",
    "    print(fit_wls.params)\n",
    "    y_regression = [fit_wls.params[0] + fit_wls.params[1]*x for x in bin_prediction_means]\n",
    "    plt.plot(bin_prediction_means, y_regression, label='Weighted Least Squares Regression', color=\"green\")\n",
    "    plt.plot(bin_prediction_means, bin_correct_means, label='Actual Calibration', color=\"#1f77b4\")\n",
    "    plt.plot((0, 1), (0, 1), label='Perfect Calibration', color=\"#ff7f0e\")\n",
    "    bin_count = brier['detail']['bin_count']\n",
    "    counts = np.array(bin_counts)\n",
    "    bins = (np.arange(bin_count) + 0.5) / bin_count\n",
    "    plt.legend(loc='upper center')\n",
    "    plt.xlabel('Predicted R')\n",
    "    plt.ylabel('Actual R')\n",
    "    plt.twinx()\n",
    "    plt.ylabel('Number of reviews')\n",
    "    plt.bar(bins, counts, width=(0.8 / bin_count), ec='k', lw=.2, alpha=0.5, label='Number of reviews')\n",
    "    plt.legend(loc='lower center')\n",
    "\n",
    "\n",
    "plot_brier(dataset['p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "plt.figure(figsize=(16, 12))\n",
    "for last_rating in (\"1\",\"2\",\"3\",\"4\"):\n",
    "    plt.subplot(2, 2, int(last_rating))\n",
    "    print(f\"\\nLast rating: {last_rating}\")\n",
    "    plot_brier(dataset[dataset['r_history'].str.endswith(last_rating)]['p'], dataset[dataset['r_history'].str.endswith(last_rating)]['y'], bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def to_percent(temp, position):\n",
    "    return '%1.0f' % (100 * temp) + '%'\n",
    "\n",
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "stability_calibration = pd.DataFrame(columns=['stability', 'predicted_retention', 'actual_retention'])\n",
    "stability_calibration = dataset[['stability', 'p', 'y']].copy()\n",
    "stability_calibration['bin'] = stability_calibration['stability'].map(lambda x: math.pow(1.2, math.floor(math.log(x, 1.2))))\n",
    "stability_group = stability_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=stability_group.index, height=stability_group['y'], width=stability_group.index / 5.5,\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Stability (days)\")\n",
    "ax1.semilogx()\n",
    "lns.append(lns1)\n",
    "\n",
    "stability_group = stability_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(stability_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(stability_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "difficulty_calibration = pd.DataFrame(columns=['difficulty', 'predicted_retention', 'actual_retention'])\n",
    "difficulty_calibration = dataset[['difficulty', 'p', 'y']].copy()\n",
    "difficulty_calibration['bin'] = difficulty_calibration['difficulty'].map(round)\n",
    "difficulty_group = difficulty_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=difficulty_group.index, height=difficulty_group['y'],\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Difficulty\")\n",
    "lns.append(lns1)\n",
    "\n",
    "difficulty_group = difficulty_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(difficulty_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(difficulty_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_92291_row0_col0, #T_92291_row0_col1, #T_92291_row0_col2, #T_92291_row0_col3, #T_92291_row0_col4, #T_92291_row0_col5, #T_92291_row0_col6, #T_92291_row0_col7, #T_92291_row1_col0, #T_92291_row1_col1, #T_92291_row1_col2, #T_92291_row1_col3, #T_92291_row1_col4, #T_92291_row1_col5, #T_92291_row1_col6, #T_92291_row2_col0, #T_92291_row2_col1, #T_92291_row2_col2, #T_92291_row2_col3, #T_92291_row2_col4, #T_92291_row2_col5, #T_92291_row2_col6, #T_92291_row3_col0, #T_92291_row3_col1, #T_92291_row3_col2, #T_92291_row3_col3, #T_92291_row3_col6, #T_92291_row4_col0, #T_92291_row4_col1, #T_92291_row4_col2, #T_92291_row4_col3, #T_92291_row5_col0, #T_92291_row5_col1, #T_92291_row5_col2, #T_92291_row6_col0, #T_92291_row6_col2, #T_92291_row7_col0, #T_92291_row7_col2, #T_92291_row8_col2, #T_92291_row10_col0, #T_92291_row10_col8, #T_92291_row11_col0, #T_92291_row11_col8, #T_92291_row12_col0, #T_92291_row12_col1, #T_92291_row12_col8, #T_92291_row13_col0, #T_92291_row13_col1, #T_92291_row13_col5, #T_92291_row13_col7, #T_92291_row13_col8, #T_92291_row14_col0, #T_92291_row14_col1, #T_92291_row14_col5, #T_92291_row14_col6, #T_92291_row14_col7, #T_92291_row14_col8, #T_92291_row15_col0, #T_92291_row15_col1, #T_92291_row15_col4, #T_92291_row15_col5, #T_92291_row15_col6, #T_92291_row15_col7, #T_92291_row15_col8 {\n",
       "  background-color: #000000;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_92291_row0_col8 {\n",
       "  background-color: #8989ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_92291_row1_col7 {\n",
       "  background-color: #ffbdbd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row1_col8, #T_92291_row6_col8, #T_92291_row8_col0 {\n",
       "  background-color: #ffe9e9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row2_col7, #T_92291_row15_col2 {\n",
       "  background-color: #a9a9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row2_col8, #T_92291_row6_col4, #T_92291_row6_col7, #T_92291_row11_col3 {\n",
       "  background-color: #fdfdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row3_col4, #T_92291_row3_col7, #T_92291_row4_col7, #T_92291_row7_col8, #T_92291_row9_col0, #T_92291_row9_col2, #T_92291_row12_col3 {\n",
       "  background-color: #e9e9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row3_col5 {\n",
       "  background-color: #ffb9b9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row3_col8, #T_92291_row5_col3 {\n",
       "  background-color: #f9f9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row4_col4 {\n",
       "  background-color: #b1b1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row4_col5, #T_92291_row8_col3, #T_92291_row11_col4, #T_92291_row11_col6, #T_92291_row12_col6 {\n",
       "  background-color: #ffeded;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row4_col6, #T_92291_row8_col4, #T_92291_row10_col3 {\n",
       "  background-color: #fffdfd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row4_col8, #T_92291_row7_col6, #T_92291_row13_col4 {\n",
       "  background-color: #fff5f5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row5_col4, #T_92291_row5_col8 {\n",
       "  background-color: #f1f1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row5_col5 {\n",
       "  background-color: #fff1f1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row5_col6, #T_92291_row6_col3 {\n",
       "  background-color: #cdcdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row5_col7, #T_92291_row6_col1, #T_92291_row10_col2 {\n",
       "  background-color: #ddddff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row6_col5, #T_92291_row7_col1, #T_92291_row9_col3 {\n",
       "  background-color: #e5e5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row6_col6 {\n",
       "  background-color: #ffc1c1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row7_col3 {\n",
       "  background-color: #c5c5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row7_col4, #T_92291_row11_col1 {\n",
       "  background-color: #d1d1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row7_col5, #T_92291_row9_col7 {\n",
       "  background-color: #ffa9a9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row7_col7 {\n",
       "  background-color: #ffd9d9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row8_col1 {\n",
       "  background-color: #d9d9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row8_col5, #T_92291_row11_col5 {\n",
       "  background-color: #ffb1b1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row8_col6 {\n",
       "  background-color: #ffe5e5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row8_col7, #T_92291_row10_col5 {\n",
       "  background-color: #ff9d9d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row8_col8, #T_92291_row9_col1, #T_92291_row13_col3 {\n",
       "  background-color: #b9b9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row9_col4, #T_92291_row9_col8, #T_92291_row12_col7 {\n",
       "  background-color: #ffd5d5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row9_col5 {\n",
       "  background-color: #ffa1a1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row9_col6, #T_92291_row12_col5 {\n",
       "  background-color: #ff9999;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row10_col1, #T_92291_row13_col6 {\n",
       "  background-color: #c9c9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row10_col4 {\n",
       "  background-color: #ffcdcd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row10_col6 {\n",
       "  background-color: #ffc9c9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row10_col7 {\n",
       "  background-color: #ff4d4d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_92291_row11_col2, #T_92291_row13_col2 {\n",
       "  background-color: #bdbdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row11_col7, #T_92291_row12_col4 {\n",
       "  background-color: #ffa5a5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row12_col2 {\n",
       "  background-color: #e1e1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_92291_row14_col2 {\n",
       "  background-color: #9999ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_92291_row14_col3 {\n",
       "  background-color: #9d9dff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_92291_row14_col4 {\n",
       "  background-color: #7d7dff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_92291_row15_col3 {\n",
       "  background-color: #6969ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_92291\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >d_bin</th>\n",
       "      <th id=\"T_92291_level0_col0\" class=\"col_heading level0 col0\" >2</th>\n",
       "      <th id=\"T_92291_level0_col1\" class=\"col_heading level0 col1\" >3</th>\n",
       "      <th id=\"T_92291_level0_col2\" class=\"col_heading level0 col2\" >4</th>\n",
       "      <th id=\"T_92291_level0_col3\" class=\"col_heading level0 col3\" >5</th>\n",
       "      <th id=\"T_92291_level0_col4\" class=\"col_heading level0 col4\" >6</th>\n",
       "      <th id=\"T_92291_level0_col5\" class=\"col_heading level0 col5\" >7</th>\n",
       "      <th id=\"T_92291_level0_col6\" class=\"col_heading level0 col6\" >8</th>\n",
       "      <th id=\"T_92291_level0_col7\" class=\"col_heading level0 col7\" >9</th>\n",
       "      <th id=\"T_92291_level0_col8\" class=\"col_heading level0 col8\" >10</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >s_bin</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "      <th class=\"blank col8\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_92291_level0_row0\" class=\"row_heading level0 row0\" >1.000000</th>\n",
       "      <td id=\"T_92291_row0_col0\" class=\"data row0 col0\" ></td>\n",
       "      <td id=\"T_92291_row0_col1\" class=\"data row0 col1\" ></td>\n",
       "      <td id=\"T_92291_row0_col2\" class=\"data row0 col2\" ></td>\n",
       "      <td id=\"T_92291_row0_col3\" class=\"data row0 col3\" ></td>\n",
       "      <td id=\"T_92291_row0_col4\" class=\"data row0 col4\" ></td>\n",
       "      <td id=\"T_92291_row0_col5\" class=\"data row0 col5\" ></td>\n",
       "      <td id=\"T_92291_row0_col6\" class=\"data row0 col6\" ></td>\n",
       "      <td id=\"T_92291_row0_col7\" class=\"data row0 col7\" ></td>\n",
       "      <td id=\"T_92291_row0_col8\" class=\"data row0 col8\" >-4.58%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_92291_level0_row1\" class=\"row_heading level0 row1\" >1.400000</th>\n",
       "      <td id=\"T_92291_row1_col0\" class=\"data row1 col0\" ></td>\n",
       "      <td id=\"T_92291_row1_col1\" class=\"data row1 col1\" ></td>\n",
       "      <td id=\"T_92291_row1_col2\" class=\"data row1 col2\" ></td>\n",
       "      <td id=\"T_92291_row1_col3\" class=\"data row1 col3\" ></td>\n",
       "      <td id=\"T_92291_row1_col4\" class=\"data row1 col4\" ></td>\n",
       "      <td id=\"T_92291_row1_col5\" class=\"data row1 col5\" ></td>\n",
       "      <td id=\"T_92291_row1_col6\" class=\"data row1 col6\" ></td>\n",
       "      <td id=\"T_92291_row1_col7\" class=\"data row1 col7\" >2.56%</td>\n",
       "      <td id=\"T_92291_row1_col8\" class=\"data row1 col8\" >0.79%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_92291_level0_row2\" class=\"row_heading level0 row2\" >1.960000</th>\n",
       "      <td id=\"T_92291_row2_col0\" class=\"data row2 col0\" ></td>\n",
       "      <td id=\"T_92291_row2_col1\" class=\"data row2 col1\" ></td>\n",
       "      <td id=\"T_92291_row2_col2\" class=\"data row2 col2\" ></td>\n",
       "      <td id=\"T_92291_row2_col3\" class=\"data row2 col3\" ></td>\n",
       "      <td id=\"T_92291_row2_col4\" class=\"data row2 col4\" ></td>\n",
       "      <td id=\"T_92291_row2_col5\" class=\"data row2 col5\" ></td>\n",
       "      <td id=\"T_92291_row2_col6\" class=\"data row2 col6\" ></td>\n",
       "      <td id=\"T_92291_row2_col7\" class=\"data row2 col7\" >-3.36%</td>\n",
       "      <td id=\"T_92291_row2_col8\" class=\"data row2 col8\" >-0.04%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_92291_level0_row3\" class=\"row_heading level0 row3\" >2.740000</th>\n",
       "      <td id=\"T_92291_row3_col0\" class=\"data row3 col0\" ></td>\n",
       "      <td id=\"T_92291_row3_col1\" class=\"data row3 col1\" ></td>\n",
       "      <td id=\"T_92291_row3_col2\" class=\"data row3 col2\" ></td>\n",
       "      <td id=\"T_92291_row3_col3\" class=\"data row3 col3\" ></td>\n",
       "      <td id=\"T_92291_row3_col4\" class=\"data row3 col4\" >-0.81%</td>\n",
       "      <td id=\"T_92291_row3_col5\" class=\"data row3 col5\" >2.78%</td>\n",
       "      <td id=\"T_92291_row3_col6\" class=\"data row3 col6\" ></td>\n",
       "      <td id=\"T_92291_row3_col7\" class=\"data row3 col7\" >-0.81%</td>\n",
       "      <td id=\"T_92291_row3_col8\" class=\"data row3 col8\" >-0.23%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_92291_level0_row4\" class=\"row_heading level0 row4\" >3.840000</th>\n",
       "      <td id=\"T_92291_row4_col0\" class=\"data row4 col0\" ></td>\n",
       "      <td id=\"T_92291_row4_col1\" class=\"data row4 col1\" ></td>\n",
       "      <td id=\"T_92291_row4_col2\" class=\"data row4 col2\" ></td>\n",
       "      <td id=\"T_92291_row4_col3\" class=\"data row4 col3\" ></td>\n",
       "      <td id=\"T_92291_row4_col4\" class=\"data row4 col4\" >-3.10%</td>\n",
       "      <td id=\"T_92291_row4_col5\" class=\"data row4 col5\" >0.71%</td>\n",
       "      <td id=\"T_92291_row4_col6\" class=\"data row4 col6\" >0.15%</td>\n",
       "      <td id=\"T_92291_row4_col7\" class=\"data row4 col7\" >-0.91%</td>\n",
       "      <td id=\"T_92291_row4_col8\" class=\"data row4 col8\" >0.44%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_92291_level0_row5\" class=\"row_heading level0 row5\" >5.380000</th>\n",
       "      <td id=\"T_92291_row5_col0\" class=\"data row5 col0\" ></td>\n",
       "      <td id=\"T_92291_row5_col1\" class=\"data row5 col1\" ></td>\n",
       "      <td id=\"T_92291_row5_col2\" class=\"data row5 col2\" ></td>\n",
       "      <td id=\"T_92291_row5_col3\" class=\"data row5 col3\" >-0.31%</td>\n",
       "      <td id=\"T_92291_row5_col4\" class=\"data row5 col4\" >-0.53%</td>\n",
       "      <td id=\"T_92291_row5_col5\" class=\"data row5 col5\" >0.59%</td>\n",
       "      <td id=\"T_92291_row5_col6\" class=\"data row5 col6\" >-1.95%</td>\n",
       "      <td id=\"T_92291_row5_col7\" class=\"data row5 col7\" >-1.39%</td>\n",
       "      <td id=\"T_92291_row5_col8\" class=\"data row5 col8\" >-0.57%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_92291_level0_row6\" class=\"row_heading level0 row6\" >7.530000</th>\n",
       "      <td id=\"T_92291_row6_col0\" class=\"data row6 col0\" ></td>\n",
       "      <td id=\"T_92291_row6_col1\" class=\"data row6 col1\" >-1.31%</td>\n",
       "      <td id=\"T_92291_row6_col2\" class=\"data row6 col2\" ></td>\n",
       "      <td id=\"T_92291_row6_col3\" class=\"data row6 col3\" >-1.99%</td>\n",
       "      <td id=\"T_92291_row6_col4\" class=\"data row6 col4\" >-0.15%</td>\n",
       "      <td id=\"T_92291_row6_col5\" class=\"data row6 col5\" >-0.97%</td>\n",
       "      <td id=\"T_92291_row6_col6\" class=\"data row6 col6\" >2.48%</td>\n",
       "      <td id=\"T_92291_row6_col7\" class=\"data row6 col7\" >-0.04%</td>\n",
       "      <td id=\"T_92291_row6_col8\" class=\"data row6 col8\" >0.91%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_92291_level0_row7\" class=\"row_heading level0 row7\" >10.540000</th>\n",
       "      <td id=\"T_92291_row7_col0\" class=\"data row7 col0\" ></td>\n",
       "      <td id=\"T_92291_row7_col1\" class=\"data row7 col1\" >-1.05%</td>\n",
       "      <td id=\"T_92291_row7_col2\" class=\"data row7 col2\" ></td>\n",
       "      <td id=\"T_92291_row7_col3\" class=\"data row7 col3\" >-2.24%</td>\n",
       "      <td id=\"T_92291_row7_col4\" class=\"data row7 col4\" >-1.84%</td>\n",
       "      <td id=\"T_92291_row7_col5\" class=\"data row7 col5\" >3.39%</td>\n",
       "      <td id=\"T_92291_row7_col6\" class=\"data row7 col6\" >0.34%</td>\n",
       "      <td id=\"T_92291_row7_col7\" class=\"data row7 col7\" >1.47%</td>\n",
       "      <td id=\"T_92291_row7_col8\" class=\"data row7 col8\" >-0.81%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_92291_level0_row8\" class=\"row_heading level0 row8\" >14.760000</th>\n",
       "      <td id=\"T_92291_row8_col0\" class=\"data row8 col0\" >0.83%</td>\n",
       "      <td id=\"T_92291_row8_col1\" class=\"data row8 col1\" >-1.50%</td>\n",
       "      <td id=\"T_92291_row8_col2\" class=\"data row8 col2\" ></td>\n",
       "      <td id=\"T_92291_row8_col3\" class=\"data row8 col3\" >0.68%</td>\n",
       "      <td id=\"T_92291_row8_col4\" class=\"data row8 col4\" >0.08%</td>\n",
       "      <td id=\"T_92291_row8_col5\" class=\"data row8 col5\" >3.10%</td>\n",
       "      <td id=\"T_92291_row8_col6\" class=\"data row8 col6\" >1.02%</td>\n",
       "      <td id=\"T_92291_row8_col7\" class=\"data row8 col7\" >3.89%</td>\n",
       "      <td id=\"T_92291_row8_col8\" class=\"data row8 col8\" >-2.73%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_92291_level0_row9\" class=\"row_heading level0 row9\" >20.660000</th>\n",
       "      <td id=\"T_92291_row9_col0\" class=\"data row9 col0\" >-0.84%</td>\n",
       "      <td id=\"T_92291_row9_col1\" class=\"data row9 col1\" >-2.66%</td>\n",
       "      <td id=\"T_92291_row9_col2\" class=\"data row9 col2\" >-0.82%</td>\n",
       "      <td id=\"T_92291_row9_col3\" class=\"data row9 col3\" >-1.09%</td>\n",
       "      <td id=\"T_92291_row9_col4\" class=\"data row9 col4\" >1.59%</td>\n",
       "      <td id=\"T_92291_row9_col5\" class=\"data row9 col5\" >3.64%</td>\n",
       "      <td id=\"T_92291_row9_col6\" class=\"data row9 col6\" >4.04%</td>\n",
       "      <td id=\"T_92291_row9_col7\" class=\"data row9 col7\" >3.32%</td>\n",
       "      <td id=\"T_92291_row9_col8\" class=\"data row9 col8\" >1.64%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_92291_level0_row10\" class=\"row_heading level0 row10\" >28.930000</th>\n",
       "      <td id=\"T_92291_row10_col0\" class=\"data row10 col0\" ></td>\n",
       "      <td id=\"T_92291_row10_col1\" class=\"data row10 col1\" >-2.13%</td>\n",
       "      <td id=\"T_92291_row10_col2\" class=\"data row10 col2\" >-1.30%</td>\n",
       "      <td id=\"T_92291_row10_col3\" class=\"data row10 col3\" >0.12%</td>\n",
       "      <td id=\"T_92291_row10_col4\" class=\"data row10 col4\" >1.93%</td>\n",
       "      <td id=\"T_92291_row10_col5\" class=\"data row10 col5\" >3.81%</td>\n",
       "      <td id=\"T_92291_row10_col6\" class=\"data row10 col6\" >2.16%</td>\n",
       "      <td id=\"T_92291_row10_col7\" class=\"data row10 col7\" >6.91%</td>\n",
       "      <td id=\"T_92291_row10_col8\" class=\"data row10 col8\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_92291_level0_row11\" class=\"row_heading level0 row11\" >40.500000</th>\n",
       "      <td id=\"T_92291_row11_col0\" class=\"data row11 col0\" ></td>\n",
       "      <td id=\"T_92291_row11_col1\" class=\"data row11 col1\" >-1.74%</td>\n",
       "      <td id=\"T_92291_row11_col2\" class=\"data row11 col2\" >-2.56%</td>\n",
       "      <td id=\"T_92291_row11_col3\" class=\"data row11 col3\" >-0.12%</td>\n",
       "      <td id=\"T_92291_row11_col4\" class=\"data row11 col4\" >0.76%</td>\n",
       "      <td id=\"T_92291_row11_col5\" class=\"data row11 col5\" >3.00%</td>\n",
       "      <td id=\"T_92291_row11_col6\" class=\"data row11 col6\" >0.72%</td>\n",
       "      <td id=\"T_92291_row11_col7\" class=\"data row11 col7\" >3.54%</td>\n",
       "      <td id=\"T_92291_row11_col8\" class=\"data row11 col8\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_92291_level0_row12\" class=\"row_heading level0 row12\" >56.690000</th>\n",
       "      <td id=\"T_92291_row12_col0\" class=\"data row12 col0\" ></td>\n",
       "      <td id=\"T_92291_row12_col1\" class=\"data row12 col1\" ></td>\n",
       "      <td id=\"T_92291_row12_col2\" class=\"data row12 col2\" >-1.15%</td>\n",
       "      <td id=\"T_92291_row12_col3\" class=\"data row12 col3\" >-0.89%</td>\n",
       "      <td id=\"T_92291_row12_col4\" class=\"data row12 col4\" >3.57%</td>\n",
       "      <td id=\"T_92291_row12_col5\" class=\"data row12 col5\" >4.04%</td>\n",
       "      <td id=\"T_92291_row12_col6\" class=\"data row12 col6\" >0.77%</td>\n",
       "      <td id=\"T_92291_row12_col7\" class=\"data row12 col7\" >1.68%</td>\n",
       "      <td id=\"T_92291_row12_col8\" class=\"data row12 col8\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_92291_level0_row13\" class=\"row_heading level0 row13\" >79.370000</th>\n",
       "      <td id=\"T_92291_row13_col0\" class=\"data row13 col0\" ></td>\n",
       "      <td id=\"T_92291_row13_col1\" class=\"data row13 col1\" ></td>\n",
       "      <td id=\"T_92291_row13_col2\" class=\"data row13 col2\" >-2.57%</td>\n",
       "      <td id=\"T_92291_row13_col3\" class=\"data row13 col3\" >-2.71%</td>\n",
       "      <td id=\"T_92291_row13_col4\" class=\"data row13 col4\" >0.34%</td>\n",
       "      <td id=\"T_92291_row13_col5\" class=\"data row13 col5\" ></td>\n",
       "      <td id=\"T_92291_row13_col6\" class=\"data row13 col6\" >-2.07%</td>\n",
       "      <td id=\"T_92291_row13_col7\" class=\"data row13 col7\" ></td>\n",
       "      <td id=\"T_92291_row13_col8\" class=\"data row13 col8\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_92291_level0_row14\" class=\"row_heading level0 row14\" >111.120000</th>\n",
       "      <td id=\"T_92291_row14_col0\" class=\"data row14 col0\" ></td>\n",
       "      <td id=\"T_92291_row14_col1\" class=\"data row14 col1\" ></td>\n",
       "      <td id=\"T_92291_row14_col2\" class=\"data row14 col2\" >-3.96%</td>\n",
       "      <td id=\"T_92291_row14_col3\" class=\"data row14 col3\" >-3.86%</td>\n",
       "      <td id=\"T_92291_row14_col4\" class=\"data row14 col4\" >-5.08%</td>\n",
       "      <td id=\"T_92291_row14_col5\" class=\"data row14 col5\" ></td>\n",
       "      <td id=\"T_92291_row14_col6\" class=\"data row14 col6\" ></td>\n",
       "      <td id=\"T_92291_row14_col7\" class=\"data row14 col7\" ></td>\n",
       "      <td id=\"T_92291_row14_col8\" class=\"data row14 col8\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_92291_level0_row15\" class=\"row_heading level0 row15\" >155.570000</th>\n",
       "      <td id=\"T_92291_row15_col0\" class=\"data row15 col0\" ></td>\n",
       "      <td id=\"T_92291_row15_col1\" class=\"data row15 col1\" ></td>\n",
       "      <td id=\"T_92291_row15_col2\" class=\"data row15 col2\" >-3.35%</td>\n",
       "      <td id=\"T_92291_row15_col3\" class=\"data row15 col3\" >-5.87%</td>\n",
       "      <td id=\"T_92291_row15_col4\" class=\"data row15 col4\" ></td>\n",
       "      <td id=\"T_92291_row15_col5\" class=\"data row15 col5\" ></td>\n",
       "      <td id=\"T_92291_row15_col6\" class=\"data row15 col6\" ></td>\n",
       "      <td id=\"T_92291_row15_col7\" class=\"data row15 col7\" ></td>\n",
       "      <td id=\"T_92291_row15_col8\" class=\"data row15 col8\" ></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x2b8546580>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "B_W_Metric_raw = dataset[['difficulty', 'stability', 'p', 'y']].copy()\n",
    "B_W_Metric_raw['s_bin'] = B_W_Metric_raw['stability'].map(lambda x: round(math.pow(1.4, math.floor(math.log(x, 1.4))), 2))\n",
    "B_W_Metric_raw['d_bin'] = B_W_Metric_raw['difficulty'].map(lambda x: int(round(x)))\n",
    "B_W_Metric = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('mean').reset_index()\n",
    "B_W_Metric_count = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('count').reset_index()\n",
    "B_W_Metric['B-W'] = B_W_Metric['p'] - B_W_Metric['y']\n",
    "n = len(dataset)\n",
    "bins = len(B_W_Metric)\n",
    "B_W_Metric_pivot = B_W_Metric[B_W_Metric_count['p'] > max(50, n / (3 * bins))].pivot(index=\"s_bin\", columns='d_bin', values='B-W')\n",
    "B_W_Metric_pivot.apply(pd.to_numeric).style.background_gradient(cmap='seismic', axis=None, vmin=-0.2, vmax=0.2).format(\"{:.2%}\", na_rep='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R_Metric:  0.04089725943586747\n",
      "R-squared: -6.8749\n",
      "RMSE: 0.1527\n",
      "[0.68927589 0.25115013]\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Universal Metric of FSRS: 0.0118\n",
      "Universal Metric of SM2: 0.0752\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def sm2(history):\n",
    "    ivl = 0\n",
    "    ef = 2.5\n",
    "    reps = 0\n",
    "    for delta_t, rating in history:\n",
    "        delta_t = delta_t.item()\n",
    "        rating = rating.item() + 1\n",
    "        if rating > 2:\n",
    "            if reps == 0:\n",
    "                ivl = 1\n",
    "                reps = 1\n",
    "            elif reps == 1:\n",
    "                ivl = 6\n",
    "                reps = 2\n",
    "            else:\n",
    "                ivl = ivl * ef\n",
    "                reps += 1\n",
    "        else:\n",
    "            ivl = 1\n",
    "            reps = 0\n",
    "        ef = max(1.3, ef + (0.1 - (5 - rating) * (0.08 + (5 - rating) * 0.02)))\n",
    "        ivl = max(1, round(ivl+0.01))\n",
    "    return ivl\n",
    "\n",
    "dataset['sm2_interval'] = dataset['tensor'].map(sm2)\n",
    "dataset['sm2_p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['sm2_interval'])\n",
    "cross_comparison = dataset[['sm2_p', 'p', 'y']].copy()\n",
    "\n",
    "R_Metric = mean_squared_error(cross_comparison['y'], cross_comparison['sm2_p'], squared=False) - mean_squared_error(cross_comparison['y'], cross_comparison['p'], squared=False)\n",
    "print(\"R_Metric: \", R_Metric)\n",
    "plot_brier(dataset['sm2_p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(6, 6))\n",
    "\n",
    "cross_comparison['SM2_B-W'] = cross_comparison['sm2_p'] - cross_comparison['y']\n",
    "cross_comparison['SM2_bin'] = cross_comparison['sm2_p'].map(lambda x: round(x, 1))\n",
    "cross_comparison['FSRS_B-W'] = cross_comparison['p'] - cross_comparison['y']\n",
    "cross_comparison['FSRS_bin'] = cross_comparison['p'].map(lambda x: round(x, 1))\n",
    "\n",
    "plt.axhline(y = 0.0, color = 'black', linestyle = '-')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='SM2_bin').agg({'y': ['mean'], 'FSRS_B-W': ['mean'], 'p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of FSRS: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['p', 'mean'], sample_weight=cross_comparison_group['p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['p', 'percent'] = cross_comparison_group['p', 'count'] / cross_comparison_group['p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['FSRS_B-W', 'mean'], s=cross_comparison_group['p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['FSRS_B-W', 'mean'], label='FSRS by SM2')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='FSRS_bin').agg({'y': ['mean'], 'SM2_B-W': ['mean'], 'sm2_p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of SM2: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['sm2_p', 'mean'], sample_weight=cross_comparison_group['sm2_p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['sm2_p', 'percent'] = cross_comparison_group['sm2_p', 'count'] / cross_comparison_group['sm2_p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['SM2_B-W', 'mean'], s=cross_comparison_group['sm2_p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['SM2_B-W', 'mean'], label='SM2 by FSRS')\n",
    "\n",
    "plt.legend(loc='lower center')\n",
    "plt.grid(linestyle='--')\n",
    "plt.title(\"SM2 vs. FSRS\")\n",
    "plt.xlabel('Predicted R')\n",
    "plt.ylabel('B-W Metric')\n",
    "plt.xlim(0, 1)\n",
    "plt.xticks(np.arange(0, 1.1, 0.1))\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "fsrs4anki",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
